The Importance of AI in life sciences

 Why is AI important for life sciences? Let's take a step back why AI is even important at this juncture in time? Three things have happened that there's a confluence of those three things. One is we now are seeing lots and lots of data regardless of the industry across the industry. The second thing is we now are at the stage are at the point that we virtually have infinite compute power thanks to the Giants of cloud computing and all the platforms that are available and the AI algorithms and analytics algorithms themselves have got to a stage that the maturity that now we can we actually see them being applied to many different scenarios. Now take that to Life Sciences and health care. A life sciences company like ours every stage of the value process we're generating a lot of data a lot of decisions need to be made by our experts. The question is how you use AI data science to equip them to make the right decision at the right time.

I've been working in the area of data science advanced analytics AI in medicine for a long time maybe 20 plus years but before I was with a more in a tech type of an environment and company and almost a year that I'm now in Novartis. Now a lot of people ask me: "Why this change? Why this move?" Although I have been operating In tech in health care and AI and data science in health care for a long time. I think is for me is the big p purpose still there. We are helping people out there who are in need of certain therapies certain basically medication certain ways of care that these kind of technologies can help with but is for me is closing the loop is in tech being innovating in health now being in core health and trying to bring tech innovation into this environment in order to make a dent in order to push the envelope. What we are doing with Microsoft in the context of the AI Innovation Lab or Center is two major components. One is we call AI exploration the other one we call AI empowerment.

What do we mean by AI exploration is bringing the world-class AI expertise that Microsoft brings to this collaboration combining it with world-class expertise in biology and medicine that we as Novartis will bring to this collaboration and then working shoulder to shoulder hand in hand to really tackle challenging problems that matter to the various parts of the value chain being a discovery development or commercial activity and so on.

We're going after initially with three use cases. One has to do with generative chemistry which is can we use AI deep learning algorithms in order to suggest molecules with certain characteristics. The second one has to do with our CAR-T Cell Therapy platform and Cell and Gene production and the precision basically production of Cell and Gene therapies and using advanced analytics and AI and the third one is in the broader space of imaging but starting with Optical Coherence Tomography OCT images of the eye and using of deep learning and AI to put precision dosing of the patients which potentially down the road could help with lowering the burden of use of those kind of medications.

Ai data science analytics cannot be scaled up unless everyone all of our associates within Novartis are somehow someway using AI and capabilities of it within the workflow of what they're doing day in day out. So for that we want to empower all of our associates and what I would like to call as citizen data scientist. So the issue is how you infuse AI into the various parts of the work flow and how you're enabling the associates to do their job better and more efficiently without AI getting in the way.

So that is the trick of it. How to bake that into the work flow and enable people. One is a fantastic cultural fit between our organization and Microsoft at every level and that is actually evident from the work and collaboration that we are embarking on. The second one is we really are bringing the best of the best in a AI and technology to the best of the best in medicine and biology.

That is a unique and very very powerful combination. And the third one is really a common objective which also ties back to that cultural element. We really want to make a dent in how we're serving people's basically well-being out there in the world and giving the hope to people. I'm off the firm belief in order to bring AI and data science into a medicine and especially a pharma company. We need the ecosystem of partners from big tech AI companies like Microsoft whom we're partnering with now to academic institutions who really innovating and pushing the envelope on AI and algorithmic work on that. Great work that is being done by those and many of those organizations to the startup community who are innovating at the intersection of AI and its application to life sciences.

This is the time to actually bring all of that to the domain of medicine and really impact this industry and this domain because of the importance of it to the humanity and what is happening to the world at large..

Read More: What’s the Best Diet? Healthy Eating 101